R/statpsych1.R
ci.stdmean.strat.Rd
Computes confidence intervals for a population standardized mean difference in a 2-group nonexperimental design with stratified random sampling (a random sample of a specified size from each subpopulation) using a square root weighted variance standardizer or single group standard deviation standardizer. Equality of variances is not assumed.
ci.stdmean.strat(alpha, m1, m2, sd1, sd2, n1, n2, p1)
alpha level for 1-alpha confidence
estimated mean for group 1
estimated mean for group 2
estimated standard deviation for group 1
estimated standard deviation for group 2
sample size for group 1
sample size for group 2
proportion of total population in subpopulation 1
Returns a 3-row matrix. The columns are:
Estimate - estimated standardized mean difference
adj Estimate - bias adjusted standardized mean difference estimate
SE - standard error
LL - lower limit of the confidence interval
UL - upper limit of the confidence interval
Bonett DG (2020). “Point-biserial correlation: Interval estimation, hypothesis testing, meta-analysis, and sample size determination.” British Journal of Mathematical and Statistical Psychology, 73(S1), 113--144. ISSN 0007-1102, doi:10.1111/bmsp.12189 .
ci.stdmean.strat(.05, 33.2, 30.8, 10.5, 11.2, 200, 200, .533)
#> Estimate adj Estimate SE LL UL
#> Weighted standardizer: 0.2215549 0.2211371 0.10052057 0.02453817 0.4185716
#> Group 1 standardizer: 0.2285714 0.2277089 0.10427785 0.02419059 0.4329523
#> Group 2 standardizer: 0.2142857 0.2277089 0.09776049 0.02267868 0.4058927
# Should return:
# Estimate adj Estimate SE LL UL
# Weighted standardizer: 0.2215549 0.2211371 0.10052057 0.02453817 0.4185716
# Group 1 standardizer: 0.2285714 0.2277089 0.10427785 0.02419059 0.4329523
# Group 2 standardizer: 0.2142857 0.2277089 0.09776049 0.02267868 0.4058927